FI:PA167 Scheduling - Course Information
PA167 Scheduling
Faculty of InformaticsSpring 2018
- Extent and Intensity
- 2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
- Teacher(s)
- doc. Mgr. Hana Rudová, Ph.D. (lecturer)
- Guaranteed by
- doc. RNDr. Eva Hladká, Ph.D.
Department of Computer Systems and Communications – Faculty of Informatics
Supplier department: Department of Computer Systems and Communications – Faculty of Informatics - Timetable
- Tue 12:00–13:50 A319
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Applied Informatics (programme FI, N-AP)
- Information Technology Security (eng.) (programme FI, N-IN)
- Information Technology Security (programme FI, N-IN)
- Bioinformatics (programme FI, N-AP)
- Information Systems (programme FI, N-IN)
- Informatics (programme FI, D-IN)
- Informatics (programme FI, M-IN)
- Informatics (programme FI, N-IN)
- Parallel and Distributed Systems (programme FI, N-IN)
- Computer Graphics (programme FI, N-IN)
- Computer Networks and Communication (programme FI, N-IN)
- Computer Systems (programme FI, N-IN)
- Embedded Systems (eng.) (programme FI, N-IN)
- Embedded Systems (programme FI, N-IN)
- Service Science, Management and Engineering (eng.) (programme FI, N-AP)
- Service Science, Management and Engineering (programme FI, N-AP)
- Social Informatics (programme FI, B-AP)
- Theoretical Informatics (programme FI, N-IN)
- Upper Secondary School Teacher Training in Informatics (programme FI, M-SS)
- Upper Secondary School Teacher Training in Informatics (programme FI, M-TV)
- Upper Secondary School Teacher Training in Informatics (programme FI, N-SS) (2)
- Artificial Intelligence and Natural Language Processing (programme FI, N-IN)
- Image Processing (programme FI, N-AP)
- Course objectives
- Course provides information about various types of scheduling problems from theoretical and especially practical perspective, it demonstrates general solution approaches for scheduling problems and the most important approaches for specific practical scheduling problems.
- Learning outcomes
- Graduate will be able to identify and describe various scheduling problems appearing in practice.
Graduate will be aware of general methods applicable to solve scheduling problems from in manufacturing and services.
Graduate will be aware of algorithms and solution methods for scheduling problems such as project planning, scheduling of flexible assembly systems, or educational timetabling.
Graduate will be able to solve scheduling problems with the help of studied algorithms and approaches. - Syllabus
- Examples, scheduling problem, Graham classification.
- General purpose scheduling procedures: dispatching rules, mathematical programming, local search, constraint programming.
- Project planning and scheduling: project representation, critical path, time/cost trade-offs, workforce constraints.
- Machine scheduling: dispatching rules, branch&bound, mathematical programming, shifting bottleneck.
- Scheduling of flexible assembly systems: paced and unpaced systems, flexible flow shop.
- Reservations: interval scheduling, reservation with slack.
- Timetabling: workforce constraints, tooling constraints, relation to interval scheduling. Educational timetabling, university course timetabling.
- Workforce scheduling.
- Literature
- PINEDO, Michael. Planning and Scheduling in Manufacturing and Services. Springer, 2005. Springer Series in Operations Research. info
- Teaching methods
- The course is taught in the form of standard lecture. Lectures are oriented on presentation of various solving methods for different types of scheduling problems. Lectures include exercises to practice studied methods. Comprehensive list of exercises related to the subject covers all studied areas and allows self-study.
- Assessment methods
- There is following expected evaluation given as a sum of points for homeworks and final written exam: A 100 and more, B 90-99, C 80-89, D 70-79, E 60-69.
There are two homeworks during a semester. It is possible to get points up to 10 points per homework. Each student is required to obtain 8 points at least from the total point of 20 points.
Final written exam consists of about 9 examples and it is possible to get up to 100 points. Exam includes questions: examples (the problem is given, the choice of method might be given, typical solution: computation of the schedule), comparisons of methods or definitions, algorithms, definitions. A list of about 240 questions is available as a source for written exams. - Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually. - Teacher's information
- http://www.fi.muni.cz/~hanka/rozvrhovani
- Enrolment Statistics (Spring 2018, recent)
- Permalink: https://is.muni.cz/course/fi/spring2018/PA167